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Related papers: Optimal strategies for identifying quasars in DESI

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The time delay between multiple images of strongly lensed quasars is a powerful tool for measuring the Hubble constant (H0). To achieve H0 measurements with higher precision and accuracy using the time delay, it is crucial to expand the…

Cosmology and Nongalactic Astrophysics · Physics 2023-12-14 C. Dawes , C. Storfer , X. Huang , G. Aldering , A. Cikota , A. Dey , D. J. Schlegel

The Dark Energy Spectroscopic Instrument (DESI) cosmology survey includes a Bright Galaxy Survey (BGS) which will yield spectra for over ten million bright galaxies (r<20.2 AB mag). The resulting sample will be valuable for both…

DESI is a groundbreaking international project to observe more than 40 million quasars and galaxies over a 5-year period to create a 3D map of the sky. This map will enable us to probe multiple aspects of cosmology, from dark energy to…

Cosmology and Nongalactic Astrophysics · Physics 2024-06-25 Julien Taran

Over the last two decades, around 300 quasars have been discovered at $z\gtrsim6$, yet only one has identified as being strongly gravitationally lensed. We explore a new approach -- enlarging the permitted spectral parameter space, while…

We present a computationally efficient galaxy archetype-based redshift estimation and spectral classification method for the Dark Energy Survey Instrument (DESI) survey. The DESI survey currently relies on a redshift fitter and spectral…

We develop and demonstrate a classification system constituted by several Support Vector Machines (SVM) classifiers, which can be applied to select quasar candidates from large sky survey projects, such as SDSS, UKIDSS, GALEX. How to…

Instrumentation and Methods for Astrophysics · Physics 2015-06-04 Nanbo Peng , Yanxia Zhang , Yongheng Zhao , Xuebing Wu

Spectral type recognition is an important and fundamental step of large sky survey projects in the data reduction for further scientific research, like parameter measurement and statistic work. It tends out to be a huge job to manually…

Instrumentation and Methods for Astrophysics · Physics 2014-04-25 Hailong Yuan , Haotong Zhang , Yanxia Zhang , Yajuan Lei , Yiqiao Dong , Yongheng Zhao

The Dark Energy Spectroscopic Instrument (DESI) has embarked on an ambitious five-year survey to explore the nature of dark energy with spectroscopy of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the…

Instrumentation and Methods for Astrophysics · Physics 2023-03-15 B. Abareshi , J. Aguilar , S. Ahlen , Shadab Alam , David M. Alexander , R. Alfarsy , L. Allen , C. Allende Prieto , O. Alves , J. Ameel , E. Armengaud , J. Asorey , Alejandro Aviles , S. Bailey , A. Balaguera-Antolínez , O. Ballester , C. Baltay , A. Bault , S. F. Beltran , B. Benavides , S. BenZvi , A. Berti , R. Besuner , Florian Beutler , D. Bianchi , C. Blake , P. Blanc , R. Blum , A. Bolton , S. Bose , D. Bramall , S. Brieden , A. Brodzeller , D. Brooks , C. Brownewell , E. Buckley-Geer , R. N. Cahn , Z. Cai , R. Canning , A. Carnero Rosell , P. Carton , R. Casas , F. J. Castander , J. L. Cervantes-Cota , S. Chabanier , E. Chaussidon , C. Chuang , C. Circosta , S. Cole , A. P. Cooper , L. da Costa , M. -C. Cousinou , A. Cuceu , T. M. Davis , K. Dawson , R. de la Cruz-Noriega , A. de la Macorra , A. de Mattia , J. Della Costa , P. Demmer , M. Derwent , A. Dey , B. Dey , G. Dhungana , Z. Ding , C. Dobson , P. Doel , J. Donald-McCann , J. Donaldson , K. Douglass , Y. Duan , P. Dunlop , J. Edelstein , S. Eftekharzadeh , D. J. Eisenstein , M. Enriquez-Vargas , S. Escoffier , M. Evatt , P. Fagrelius , X. Fan , K. Fanning , V. A. Fawcett , S. Ferraro , J. Ereza , B. Flaugher , A. Font-Ribera , J. E. Forero-Romero , C. S. Frenk , S. Fromenteau , B. T. Gänsicke , C. Garcia-Quintero , L. Garrison , E. Gaztañaga , F. Gerardi , H. Gil-Marín , S. Gontcho A Gontcho , Alma X. Gonzalez-Morales , G. Gonzalez-de-Rivera , V. Gonzalez-Perez , C. Gordon , O. Graur , D. Green , C. Grove , D. Gruen , G. Gutierrez , J. Guy , C. Hahn , S. Harris , D. Herrera , Hiram K. Herrera-Alcantar , K. Honscheid , C. Howlett , D. Huterer , V. Iršič , M. Ishak , P. Jelinsky , L. Jiang , J. Jimenez , Y. P. Jing , R. Joyce , E. Jullo , S. Juneau , N. G. Karaçaylı , M. Karamanis , A. Karcher , T. Karim , R. Kehoe , S. Kent , D. Kirkby , T. Kisner , F. Kitaura , S. E. Koposov , A. Kovács , A. Kremin , Alex Krolewski , B. L'Huillier , O. Lahav , A. Lambert , C. Lamman , Ting-Wen Lan , M. Landriau , S. Lane , D. Lang , J. U. Lange , J. Lasker , L. Le Guillou , A. Leauthaud , A. Le Van Suu , Michael E. Levi , T. S. Li , C. Magneville , M. Manera , Christopher J. Manser , B. Marshall , W. McCollam , P. McDonald , Aaron M. Meisner , J. Mena-Fernández M. Mezcua , T. Miller , R. Miquel , P. Montero-Camacho , J. Moon , J. Paul Martini , J. Meneses-Rizo , J. Moustakas , E. Mueller , Andrea Muñoz-Gutiérrez , Adam D. Myers , S. Nadathur , J. Najita , L. Napolitano , E. Neilsen , Jeffrey A. Newman , J. D. Nie , Y. Ning , G. Niz , P. Norberg , Hernán E. Noriega , T. O'Brien , A. Obuljen , N. Palanque-Delabrouille , A. Palmese , P. Zhiwei , D. Pappalardo , X. Peng , W. J. Percival , S. Perruchot , R. Pogge , C. Poppett , A. Porredon , F. Prada , J. Prochaska , R. Pucha , A. Pérez-Fernández , I. Pérez-Ráfols , D. Rabinowitz , A. Raichoor , S. Ramirez-Solano , César Ramírez-Pérez , C. Ravoux , K. Reil , M. Rezaie , A. Rocher , C. Rockosi , N. A. Roe , A. Roodman , A. J. Ross , G. Rossi , R. Ruggeri , V. Ruhlmann-Kleider , C. G. Sabiu , S. Safonova , K. Said , A. Saintonge , Javier Salas Catonga , L. Samushia , E. Sanchez , C. Saulder , E. Schaan , E. Schlafly , D. Schlegel , J. Schmoll , D. Scholte , M. Schubnell , A. Secroun , H. Seo , S. Serrano , Ray M. Sharples , Michael J. Sholl , Joseph Harry Silber , D. R. Silva , M. Sirk , M. Siudek , A. Smith , D. Sprayberry , R. Staten , B. Stupak , T. Tan , Gregory Tarlé , Suk Sien Tie , R. Tojeiro , L. A. Ureña-López , F. Valdes , O. Valenzuela , M. Valluri , M. Vargas-Magaña , L. Verde , M. Walther , B. Wang , M. S. Wang , B. A. Weaver , C. Weaverdyck , R. Wechsler , Michael J. Wilson , J. Yang , Y. Yu , S. Yuan , Christophe Yèche , H. Zhang , K. Zhang , Cheng Zhao , Rongpu Zhou , Zhimin Zhou , H. Zou , J. Zou , S. Zou , Y. Zu

We apply a convolutional neural network (CNN) to classify and detect quasars in the Sloan Digital Sky Survey Stripe 82 and also to predict the photometric redshifts of quasars. The network takes the variability of objects into account by…

Instrumentation and Methods for Astrophysics · Physics 2018-04-11 Johanna Pasquet-Itam , Jérôme Pasquet

The scientific value of the next generation of large continuum surveys would be greatly increased if the redshifts of the newly detected sources could be rapidly and reliably estimated. Given the observational expense of obtaining…

Cosmology and Nongalactic Astrophysics · Physics 2021-03-03 S. J. Curran , J. P. Moss , Y. C. Perrott

Gravitationally lensed (GL) quasars are brighter than their unlensed counterparts and produce images with distinctive morphological signatures. Past searches and target selection algorithms, in particular the Sloan Quasar Lens Search…

Astrophysics of Galaxies · Physics 2015-06-23 Adriano Agnello , Brandon C. Kelly , Tommaso Treu , Philip J. Marshall

Context. Ongoing and upcoming large spectroscopic surveys are drastically increasing the number of observed quasar spectra, requiring the development of fast and accurate automated methods to estimate spectral continua. Aims. This study…

We present a catalog of 1.4 million photometrically-selected quasar candidates in the southern hemisphere over the $\sim 5000\,{\rm deg^2}$ Dark Energy Survey (DES) wide survey area. We combine optical photometry from the DES second data…

Astrophysics of Galaxies · Physics 2022-12-28 Qian Yang , Yue Shen

Studying the cosmological sources at their cosmological rest-frames is crucial to track the cosmic history and properties of compact objects. In view of the increasing data volume of existing and upcoming telescopes/detectors, we here…

High Energy Astrophysical Phenomena · Physics 2022-01-11 F. Rastegar Nia , M. T. Mirtorabi , R. Moradi , A. Vafaei. Sadr , Y. Wang

Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of hyperspectral data make the accurate classification of such data challenging for traditional machine…

Image and Video Processing · Electrical Eng. & Systems 2019-10-30 Shutao Li , Weiwei Song , Leyuan Fang , Yushi Chen , Pedram Ghamisi , Jón Atli Benediktsson

We aim to select quasar candidates based on the two large survey databases, Pan-STARRS and AllWISE. Exploring the distribution of quasars and stars in the color spaces, we find that the combination of infrared and optical photometry is more…

Instrumentation and Methods for Astrophysics · Physics 2019-03-20 Xin Jin , Yanxia Zhang , Jingyi Zhang , Yongheng Zhao , Xue-bing Wu , Dongwei Fan

We present a machine learning search for high-redshift ($5.0 < z < 6.5$) quasars using the combined photometric data from the DESI Imaging Legacy Surveys and the WISE survey. We explore the imputation of missing values for high-redshift…

Astrophysics of Galaxies · Physics 2024-09-05 Guangping Ye , Huanian Zhang , Qingwen Wu